Research on Game Theory-based VM Placement in Cloud Computing focuses on optimizing the allocation of virtual machines (VMs) across physical servers through strategic and intelligent decision-making models. This area applies game-theoretic principles to model interactions among cloud providers, users, and virtual resources to achieve efficient utilization, cost reduction, and performance balance. Key research directions include non-cooperative and cooperative game models for VM placement optimization, auction-based VM allocation strategies, and Nash equilibrium-based approaches for achieving fairness and stability in resource distribution. Other emerging topics involve multi-objective game formulations for minimizing energy consumption and migration overhead, Stackelberg games for hierarchical VM placement control, and evolutionary games for adaptive resource management in dynamic cloud environments. Additionally, integrating machine learning with game theory for predictive and self-optimizing VM placement, designing incentive-compatible mechanisms for resource sharing, and applying game models in multi-cloud and edge–cloud federations represent significant areas for future exploration.